ABSTRACT Possible interference of vamin nutritional solution with the activity of several B-lactam antibiotics against E.coli was evaluated in vitro.In Minimal basal salts-glucose medium rapid growth inhibition of sensitive E. coli was induced by 4 µg/ml of ampicillin / cloxaillin, 8 µg/ml of ampicillin, 6 µg/ml of carbencillin, hostacillin, and cephalotin, and by 32 µg/ml of penicillin G and cloxacillin. Significant inactivation of up to 32 µg/ml of carbencillin, cephalotin, penicillin G, and hostacillin was induced by addition of 1:20 v/v vamin. This inactivation was due to the presence of specific amino acids in the mixture. Deletions of amino acids revealed that valine, leucine, isoleucine, tyrosine, tryptophan, phenylalanine, cys

A simple, rapid spectrophotometric method has been established for the determination of chlorpromazine hydrochloride (CPZ) in its pure form and in a tablet formulations. The  suggested  method  is  based  on  the  oxidative coupling  reaction  with4-nitroainlline using KIO₃ in acidic solution to produce a violet colored product with maximum absorption at λ=526 nm.The  analytical data  obtained  throughout  this  study  could  be  summarid  as  follows:  1ml of 1M HCl (pH=2.2), 1 ml  of  4-nitroanilline (1x10^-2M), and 1.5ml  of (1x10^-2)KIO₃ per 25 ml reaction medium. The order of a

Concrete filled steel tube (CFST) columns are being popular in civil engineering due to their superior structural characteristics. This paper investigates enhancement in axial behavior of CFST columns by adding steel fibers to plain concrete that infill steel tubes. Four specimens were prepared: two square columns (100*100 mm) and two circular columns (100 mm in diameter). All columns were 60 cm in length. Plain concrete mix and concrete reinforced with steel fibers were used to infill steel tube columns. Ultimate axial load capacity, ductility and failure mode are discussed in this study. The results showed that the ultimate axial load capacity of CFST columns reinforced with steel fibers increased by 28% and 20 % for circular and square c

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement.

Consequently, HS